Figure 1.
Path coefficients
| Path | Path coefficient | T-Statistics | P-Values | |
|---|---|---|---|---|
| Pro growth penetration strategy → Sales network power | 0.175 | 2.350 | 0.019 | 0.465 |
| Transactive memory system → Sales network power | 0.155 | 1.977 | 0.040 | 0.465 |
| Sales network power → Sales performance | 0.110 | 1.429 | 0.154 | 0.377 |
| Pro growth penetration strategy → Sales performance | 0.233 | 3.492 | 0.001 | 0.377 |
| Transactive memory system → Pro growth penetration strategy | 0.180 | 2.462 | 0.014 | 0.342 |
| Social commerce investment → Pro growth penetration strategy | 0.125 | 1.771 | 0.077 | 0.342 |
Key characteristics of e-commerce and social commerce
| Aspect | e-Commerce | S-Commerce |
|---|---|---|
| Promotion System | Centralized by the platform | Handled by sellers, content-based and driven by affiliates/influencers |
| Promotion Cost | Often shared with the platform | Fully borne by sellers (endorsement fees, content production, advertising) |
| Influencer Requirement | Not mandatory | Often, a key success factor (live streaming, product reviews, affiliate marketing) |
| Type of Promotional Content | Images, product descriptions, and tex-tbased promotions | Short videos, live streaming, and real-time interaction |
| Consumer Engagement | Passive, more transactional | Active, emotional, driven by relationships and entertainment |
| Time & HR Investment | Relatively low, manageable by individuals | High requires a dedicated team for content, live sessions, and customer engagement |
| Promotion Scalability | Limited by the search algorithm | High if the content goes viral or receives algorithmic support from the platform |
| Sales System | Static relies on consumer search | Dynamic, can happen instantly during content exposure |
Convergent validity and reliability results
| Constructs | Loadings | AVE | Cronbach's Alpha | Composite Reliability |
|---|---|---|---|---|
| Social commerce Investment (ElAydi, 2018) | 0.737 | 0.882 | 0.918 | |
| SCI1: We create and maintain an online community around our fashion brand. | 0.824 | |||
| SCI2: We often share photos or videos of our fashion products on social media. | 0.890 | |||
| SCI3: We collaborate with influencers to improve the credibility of our brand. | 0.894 | |||
| Pro-Growth Penetration Strategy (Goeyardi et al., 2022; Umniyyatul & Aprianingsih, 2023) | 0.619 | 0.729 | 0.866 | |
| PPS1: We offer competitive pricing strategies to attract new customers. | 0.849 | |||
| PPS2: We develop new product variants to meet customer needs. | 0.722 | |||
| PPS3: We optimize distribution channels to reach wider audiences. | 0.720 | |||
| PPS4: We promote our fashion brand consistently through online marketing channels. | 0.845 | |||
| Sales performance (Komunda et al., 2023; Shapiro & Gómez, 2014) | 0.614 | 0.701 | 0.714 | |
| SP1: The number of units sold has increased. | 0.800 | |||
| SP2: Our sales revenue keeps growing. | 0.751 | |||
| SP3: More customers choose our products over competitors. | 0.799 | |||
| Transactive memory system (Nawata et al., 2020) | 0.622 | 0.713 | 0.739 | |
| TMS1: Our team knows who has expertise in specific areas. | 0.806 | |||
| TMS2: We share a clear understanding of who is responsible for which tasks. | 0.830 | |||
| TMS3: Team members know whom to ask when they need support or information. | 0.726 | |||
| Sales network power (Ferdinand & Zuhroh, 2022) | 0.621 | 0.699 | 0.767 | |
| SNP1: We are always good at the speed of delivery to our customers. | 0.709 | |||
| SNP2: We are more attractive to our business partners in our business network. | 0.890 | |||
| SNP3: We are both dependent on the other to be successful. | 0.754 |
Collinearity results
| Path | VIF |
|---|---|
| Pro growth penetration strategy → Sales network power | 1.038 |
| Pro growth penetration strategy → Sales performance | 1.044 |
| Sales network power → Sales performance | 1.040 |
| Social commerce investment → Pro growth penetration strategy | 1.006 |
| Transactive memory system → Pro growth penetration strategy | 1.007 |
| Transactive memory system → Sales network power | 1.035 |
Discriminant validity (Fornell-Larcker)
| Constructs | PPS | SNP | SP | SCI | TMS |
|---|---|---|---|---|---|
| PPS | 0.787 | - | - | - | - |
| SNP | 0.204 | 0.788 | - | - | - |
| SP | 0.255 | 0.157 | 0.784 | - | - |
| SCI | 0.140 | 0.190 | 0.047 | 0.858 | - |
| TMS | 0.191 | 0.188 | 0.149 | 0.082 | 0.786 |